Skip to main content
Glama
dheimgartner

mcpme

by dheimgartner
OverviewSchemaSourceRelated ServersScoreDiscussionsAdmin
Python
Local

mcpme

A personal MCP server that exposes your CV so any MCP-compatible agent can answer questions about you.

Demo

Install

# Create a local virtual environment and install dependencies
uv venv
uv sync .

# Or install globally as a tool
uv tool install .

Related MCP server: personal-resume-agent

Usage

By default the bundled cv.md is used. Point to your own CV with an env var:

MCPME_CV_PATH=/path/to/your-cv.md mcpme

Connect to Claude Code

To connect the server to a specific project, create a local settings file:

cat > .mcp.json << 'EOF'
{
  "mcpServers": {
    "mcpme": {
      "command": "mcpme",
      "env": {
        "MCPME_CV_PATH": "/path/to/your-cv.md"
      }
    }
  }
}
EOF

Or add it to your global ~/.claude/settings.json to make it available everywhere.

What it exposes

Type

Name

Description

Tool

read_cv

Returns the full CV text

Resource

cv://resume

CV as an MCP resource

Prompt

about_me

Primed prompt for CV Q&A

Available Tools

1 tool
read_cvA

Return the owner's full CV / résumé. Use this to answer questions about the person's background, skills, and experience.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.3/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must carry the load. It states the action ('return') but does not explicitly mention side effects, permissions, or read-only nature. Since it is a simple retrieval, the omission is acceptable, but it lacks extra contextual behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise, using two sentences with no redundant wording. The primary purpose is stated first, and the usage context is provided immediately after.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (no parameters, straightforward return of CV), the description fully covers what it does and when to use it. No additional information is necessary for the agent to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has no parameters, meaning all parameters are documented (none). The description adds no parameter information, and the baseline for high coverage is 3. No additional meaning is required.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('return') and resource ('full CV'), making it unambiguous. It also indicates its use for answering background, skills, and experience questions, which adds clarity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly provides guidance on when to use the tool: 'Use this to answer questions about the person's background, skills, and experience.' This is clear and actionable, even without alternatives to compare.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 1 tool updatev0.1.0
    • First observedread_cv
Install Server
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

A4.1/5.0
Disambiguation5/5

With only a single tool, there is no possibility of ambiguity or overlapping functionality. The tool's purpose is clearly distinct by default.

Naming Consistency5/5

The single tool name 'read_cv' uses a clear snake_case verb-object structure that is consistent and intuitive for its function.

Tool Count2/5

Having only one tool falls well below the typical 3-15 range and feels thin for a server purporting to represent a person's overall background and skills.

Completeness2/5

The domain of a personal assistant server would reasonably include additional capabilities like listing skills, providing contact details, or describing projects. Providing only a CV leaves significant gaps.

Maintenance

ActivityMaintained
ResponsivenessResponsive

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Connectors

Related MCP Servers

  • personal-context

    Ayush7614
    A
    license
    Not graded
    quality
    C
    maintenance
    Aggregates your digital footprint (GitHub, blogs, resume) into a single AI-readable profile and exposes it via MCP tools so AI agents can query your context live.
    1
    MIT

  • personal-resume-agent

    vsiwach
    A
    license
    Not graded
    quality
    D
    maintenance
    Exposes a personalized AI agent that reads your resume and provides intelligent responses about your professional background through a standardized MCP server interface with RAG capabilities.
    MIT

  • mcp-me

    fe-m-bueno
    A
    license
    Not graded
    quality
    C
    maintenance
    Transforms professional data (CV, projects) into MCP tools for LLMs to query, list, match job descriptions, and ask about experience.
    93
    MIT

  • resume-mcp

    suryakapila
    F
    license
    A
    quality
    B
    maintenance
    MCP server that exposes a resume as callable tools and resources, enabling AI agents to query experience, skills, projects, and contact information via natural language.
    3
    -

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/dheimgartner/mcpme'

If you have feedback or need assistance with the MCP directory API, please join our Discord server